ggplot( top20_breaches_2024, aes(x = records_lost, y = reorder(organisation, records_lost)) ) + geom_point(size = 5, aes(color = sector)) + # label for Ticketmaster geom_text_repel( data = top_lab, aes(label = label_text), direction = "x", hjust = 0, min.segment.length = Inf, segment.size = 0, box.padding = 0.1, point.padding = 0.2, seed = 123 ) + # use Okabe–Ito (color-blind friendly) scale_color_manual(values = okabe_ito) + # force the axis you want, keep extra room for the label scale_x_continuous( trans = "log10", breaks = breaks_vec, labels = labels_vec, expand = expansion(mult = c(0.02, 0.28)) ) + coord_cartesian(clip = "off") + labs( title = "Figure 2. Principales filtraciones de datos de 2024", x = "Records Lost", y = NULL, color = "Sector", caption = "Source: McCandless, D. (2022). Los mayores casos de filtración y piratería informática del mun" ) + # ---- apply your global figure styling ---- theme( plot.title = element_text(size = rel(1.2)), axis.title = element_text(size = rel(1.0)), legend.position = "right", # match Fig. 1 caption alignment & spacing control plot.caption.position = "plot", plot.caption = element_text(hjust = 1, margin = margin(t = 20)), # optional: lighten grid to match your fig 1 feel panel.grid.major.y = element_line(linetype = "dashed", color = "gray80"), panel.grid.major.x = element_blank(), panel.grid.minor.x = element_blank() )

Callum Waite

Bio

Callum is an ecological data analyst with a Masters in Quantitative Biology. He has a background in population ecology modelling and is passionate about effective and aesthetic data visualisation. As a data analyst with the ALA, he works on projects that support biosecurity and improve data visualisation using ALA data.

Posts

Combining multiple species distributions on one map with hexagons and points
Visualising multiple species distributions in a single figure can be difficult if there are areas where ranges overlap. In this post we introduce a way to show several species distributions in an area at once using a novel twist on the commonly used hexbin map.